The use of computing devices, including desktop computer, laptops, tablets, and mobile phones, has increased dramatically over the last few decades. Many occupations require some form of computer work and sometimes the same individual will continue to use a computing device at home for leisure. Without proper ergonomic assessments or interventions, the users of these computing devices may be subjecting themselves to poor posture and potential musculoskeletal injuries.
There has been substantial research and guidelines surrounding the use of traditional desktop computers but much of this research does not apply to mobile computing devices. Much of the current research investigating computer and mobile device usage have used sitting postures, short task durations including breaks, and have not observed the frequency of postural changes. This research is not representative of the frequency and duration of mobile device usage from modern day users.
Recent research has discovered that prolonged use of mobile devices can lead to poor posture, particularly a forward-tilted head posture that puts increased stress on cervical vertebrae. This poor posture can be caused by users hunching over and flexing their neck forward when using their mobile device for prolonged periods. The weight seen by the spine dramatically increases when flexing the head forward at varying degrees. Loss of the natural curve of the cervical spine leads to incrementally increased stresses about the cervical spine. These stresses may lead to early wear, tear, degeneration, and possibly surgeries. Mobile devices are also more frequently used by teenagers and youths who are still developing their musculoskeletal system. Forward-tilted head posture has also been shown to promote changes in heart rate and breathing.
There have been several human head and face tracking solutions for monitoring or improving posture when using a mobile device. All of these solutions have various problems. Some of them cannot work in real-time, others are not robust enough. Some methods even need special equipment in their application, such as an IR camera to locate and track pupils by highlighting them in images.
Liu, J., Liu, C. & Zhao, Z. (2012). “Head gesture recognition based on LK algorithm and GentleBost”. Advances in Information Sciences and Service Sciences, (4), 4, 158-167 (hereinafter referred to as Liu et al.) describes the use of nostril tracking to monitor human head movements such as nodding, shaking, bowing, etc. Nostril tracking is found to be robust as nostril shape does not change with age, race or gender.